Today we're joined by Abdul Fatir Ansari, a machine learning scientist at AWS AI Labs in Berlin, to discuss his paper, "Chronos: Learning the Language of Time Series." Fatir explains the challenges of leveraging pre-trained language models for time series forecasting. We explore the advantages of Chronos over statistical models, as well as its promising results in zero-shot forecasting benchmarks. Finally, we address critiques of Chronos, the ongoing research to improve synthetic data quality, and the potential for integrating Chronos into production systems.
The complete show notes for this episode can be found at twimlai.com/go/685.
Chronos: Learning the Language of Time Series with Abdul Fatir Ansari - #685 | The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) - Listen or read transcript on Metacast
